2 papers
cs.CV2024
TAPTR: Tracking Any Point with Transformers as Detection
Hongyang Li, Hao Zhang, Shilong Liu +4
In this paper, we propose a simple and strong framework for Tracking Any Point with TRansformers (TAPTR). Based on the observation that point tracking bears a great resemblance to…
cond-mat.mtrl-sci2024
Crystal Transformer Based Universal Atomic Embedding for Accurate and Transferable Prediction of Materials Properties
Luozhijie Jin, Zijian Du, Le Shu +2
In this work, we propose a novel approach to generate universal atomic embeddings, significantly enhancing the representational and accuracy aspects of atomic embeddings, which ult…